Using Wearable Activity Trackers to Predict Type 2 Diabetes: Machine Learning–Based Cross-sectional Study of the UK Biobank Accelerometer Cohort

BACKGROUND: Between 2013 and 2015, the UK Biobank collected accelerometer traces from 103,712 volunteers aged between 40 and 69 years using wrist-worn triaxial accelerometers for 1 week. This data set has been used in the past to verify that individuals with chronic diseases exhibit reduced activity...

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Detalles Bibliográficos
Autores principales: Lam, Benjamin, Catt, Michael, Cassidy, Sophie, Bacardit, Jaume, Darke, Philip, Butterfield, Sam, Alshabrawy, Ossama, Trenell, Michael, Missier, Paolo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080299/
https://www.ncbi.nlm.nih.gov/pubmed/33739298
http://dx.doi.org/10.2196/23364

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080299/
https://www.ncbi.nlm.nih.gov/pubmed/33739298
http://dx.doi.org/10.2196/23364

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